Chromosome-bound mitotic factors: release by endonucleases. - R. C. Adlakha; C. G. Sahasrabuddhe; David A. Wright; W. F. Lindsey; M. L. Smith; Rajesh P. N. Rao (Nucleic Acids Res., 1982)

Seeing Behind Occlusions. - Dana H. Ballard; Rajesh P. N. Rao (ECCV (1), 1994)

Learning Saccadic Eye Movements Using Multiscale Spatial Filters. - Rajesh P. N. Rao; Dana H. Ballard (NIPS, 1994)

Upward Separation for FewP and Related Classes. - Rajesh P. N. Rao; Jörg Rothe; Osamu Watanabe 001 (Inf. Process. Lett., 1994)

Towards a Functional Theory of Vision Based on Visual Routines. - Dana H. Ballard; Rajesh P. N. Rao (DAGM-Symposium, 1995)

Object Indexing Using an Iconic Sparse Distributed Memory. - Rajesh P. N. Rao; Dana H. Ballard (ICCV, 1995)

Natural Basis Functions and Topographic Memory for Face Recognition. - Rajesh P. N. Rao; Dana H. Ballard (IJCAI, 1995)

Modeling Saccadic Targeting in Visual Search. - Rajesh P. N. Rao; Gregory J. Zelinsky; Mary M. Hayhoe; Dana H. Ballard (NIPS, 1995)

An Active Vision Architecture Based on Iconic Representations. - Rajesh P. N. Rao; Dana H. Ballard (Artif. Intell., 1995)

A Note on P-Selective Sets and Closeness. - Rajesh P. N. Rao (Inf. Process. Lett., 1995)

Dynamic Appearance-Based Recognition. - Rajesh P. N. Rao (CVPR, 1997)

Correlates of Attention in a Model of Dynamic Visual Recognition. - Rajesh P. N. Rao (NIPS, 1997)

Dynamic Model of Visual Recognition Predicts Neural Response Properties in the Visual Cortex. - Rajesh P. N. Rao; Dana H. Ballard (Neural Comput., 1997)

Learning Lie Groups for Invariant Visual Perception. - Rajesh P. N. Rao; Daniel L. Ruderman (NIPS, 1998)

Hierarchical Learning of Navigational Behaviors in an Autonomous Robot using a Predictive Sparse Distributed Memory. - Rajesh P. N. Rao; Olac Fuentes (Mach. Learn., 1998)

Predictive Sequence Learning in Recurrent Neocortical Circuits. - Rajesh P. N. Rao; Terrence J. Sejnowski (NIPS, 1999)

A single-spike model of predictive coding. - Dana H. Ballard; Rajesh P. N. Rao; Zuohua Zhang (Neurocomputing, 2000)

Corrigendum to "Upward separation for FewP and related classes". - Rajesh P. N. Rao; Jörg Rothe; Osamu Watanabe 001 (Inf. Process. Lett., 2000)

Optimal Smoothing in Visual Motion Perception. - Rajesh P. N. Rao; David M. Eagleman; Terrence J. Sejnowski (Neural Comput., 2001)

Spike-Timing-Dependent Hebbian Plasticity as Temporal Difference Learning. - Rajesh P. N. Rao; Terrence J. Sejnowski (Neural Comput., 2001)

A Bilinear Model for Sparse Coding. - David B. Grimes; Rajesh P. N. Rao (NIPS, 2002)

Probabilistic Bilinear Models for Appearance-Based Vision. - David B. Grimes; Aaron P. Shon; Rajesh P. N. Rao (ICCV, 2003)

Learning temporal patterns by redistribution of synaptic efficacy. - Aaron P. Shon; Rajesh P. N. Rao (Neurocomputing, 2003)

Hierarchical Bayesian Inference in Networks of Spiking Neurons. - Rajesh P. N. Rao (NIPS, 2004)

Dynamic Bayesian Networks for Brain-Computer Interfaces. - Pradeep Shenoy; Rajesh P. N. Rao (NIPS, 2004)

Bayesian Computation in Recurrent Neural Circuits. - Rajesh P. N. Rao (Neural Comput., 2004)

Real-Time Classification of Electromyographic Signals for Robotic Control. - Beau Crawford; Kai J. Miller; Pradeep Shenoy; Rajesh P. N. Rao (AAAI, 2005)

Learning dynamic humanoid motion using predictive control in low dimensional subspaces. - Rawichote Chalodhorn; David B. Grimes; Gabriel Y. Maganis; Rajesh P. N. Rao (Humanoids, 2005)

Robotic imitation from human motion capture using Gaussian processes. - Aaron P. Shon; Keith Grochow; Rajesh P. N. Rao (Humanoids, 2005)

Probabilistic Gaze Imitation and Saliency Learning in a Robotic Head. - Aaron P. Shon; David B. Grimes; Chris L. Baker; Matthew W. Hoffman; Shengli Zhou; Rajesh P. N. Rao (ICRA, 2005)

Learning Shared Latent Structure for Image Synthesis and Robotic Imitation. - Aaron P. Shon; Keith Grochow; Aaron Hertzmann; Rajesh P. N. Rao (NIPS, 2005)

Goal-Based Imitation as Probabilistic Inference over Graphical Models. - Deepak Verma; Rajesh P. N. Rao (NIPS, 2005)

Learning temporal clusters with synaptic facilitation and lateral inhibition. - Chris L. Baker; Aaron P. Shon; Rajesh P. N. Rao (Neurocomputing, 2005)

Implementing belief propagation in neural circuits. - Aaron P. Shon; Rajesh P. N. Rao (Neurocomputing, 2005)

Bilinear Sparse Coding for Invariant Vision. - David B. Grimes; Rajesh P. N. Rao (Neural Comput., 2005)

Learning Humanoid Motion Dynamics through Sensory-motor Mapping in Reduced Dimensional Spaces. - Rawichote Chalodhorn; David B. Grimes; Gabriel Y. Maganis; Rajesh P. N. Rao; Minoru Asada (ICRA, 2006)

Planning and Acting in Uncertain Environments using Probabilistic Inference. - Deepak Verma; Rajesh P. N. Rao (IROS, 2006)

Learning Nonparametric Models for Probabilistic Imitation. - David B. Grimes; Daniel R. Rashid; Rajesh P. N. Rao (NIPS, 2006)

Dynamic Imitation in a Humanoid Robot through Nonparametric Probabilistic Inference. - David B. Grimes; Rawichote Chalodhorn; Rajesh P. N. Rao (Robotics: Science and Systems, 2006)

A probabilistic model of gaze imitation and shared attention. - Matthew W. Hoffman; David B. Grimes; Aaron P. Shon; Rajesh P. N. Rao (Neural Networks, 2006)

Active Imitation Learning. - Aaron P. Shon; Deepak Verma; Rajesh P. N. Rao (AAAI, 2007)

Imitation Learning Using Graphical Models. - Deepak Verma; Rajesh P. N. Rao (ECML, 2007)

Towards a Real-Time Bayesian Imitation System for a Humanoid Robot. - Aaron P. Shon; Joshua J. Storz; Rajesh P. N. Rao (ICRA, 2007)

Learning to Walk through Imitation. - Rawichote Chalodhorn; David B. Grimes; Keith Grochow; Rajesh P. N. Rao (IJCAI, 2007)

Learning full-body motions from monocular vision: dynamic imitation in a humanoid robot. - Jeffrey B. Cole; David B. Grimes; Rajesh P. N. Rao (IROS, 2007)

A Cognitive Model of Imitative Development in Humans and Machines. - Aaron P. Shon; Joshua J. Storz; Andrew N. Meltzoff; Rajesh P. N. Rao (Int. J. Humanoid Robotics, 2007)

Learning the Lie Groups of Visual Invariance. - Xu Miao; Rajesh P. N. Rao (Neural Comput., 2007)

Real-time functional brain mapping using electrocorticography. - Kai J. Miller; Marcel den Nijs; Pradeep Shenoy; John W. Miller; Rajesh P. N. Rao; Jeffrey G. Ojemann (NeuroImage, 2007)

Feasibility and pragmatics of classifying working memory load with an electroencephalograph. - David B. Grimes; Desney S. Tan; Scott E. Hudson; Pradeep Shenoy; Rajesh P. N. Rao (CHI, 2008)

Learning nonparametric policies by imitation. - David B. Grimes; Rajesh P. N. Rao (IROS, 2008)

Beyond the Gamma Band: The Role of High-Frequency Features in Movement Classification. - Kai J. Miller; Pradeep Shenoy; Marcel den Nijs; Larry B. Sorensen; Rajesh P. N. Rao; Jeffrey G. Ojemann (IEEE Trans. Biomed. Eng., 2008)

Online Electromyographic Control of a Robotic Prosthesis. - Pradeep Shenoy; Kai J. Miller; Beau Crawford; Rajesh P. N. Rao (IEEE Trans. Biomed. Eng., 2008)

Generalized Features for Electrocorticographic BCIs. - Pradeep Shenoy; Kai J. Miller; Jeffrey G. Ojemann; Rajesh P. N. Rao (IEEE Trans. Biomed. Eng., 2008)

Large Margin Boltzmann Machines. - Xu Miao; Rajesh P. N. Rao (IJCAI, 2009)

Using eigenposes for lossless periodic human motion imitation. - Rawichote Chalodhorn; Rajesh P. N. Rao (IROS, 2009)

Statistical analysis of the Indus script using $n$-grams - Nisha Yadav; Hrishikesh Joglekar; Rajesh P. N. Rao; Mayank N. Vahia; Iravatham Mahadevan; Ronojoy Adhikari (CoRR, 2009)

A Markov model of the Indus script. - Rajesh P. N. Rao; Nisha Yadav; Mayank N. Vahia; Hrishikesh Joglekar; Ronojoy Adhikari; Iravatham Mahadevan (Proc. Natl. Acad. Sci. USA, 2009)

Learning Actions through Imitation and Exploration: Towards Humanoid Robots That Learn from Humans. - David B. Grimes; Rajesh P. N. Rao (Creating Brain-Like Intelligence, 2009)

Imitation learning with hierarchical actions. - Abram L. Friesen; Rajesh P. N. Rao (ICDL, 2010)

A rational decision making framework for inhibitory control. - Pradeep Shenoy; Rajesh P. N. Rao; Angela J. Yu (NIPS, 2010)

Learning to Walk by Imitation in Low-Dimensional Subspaces. - Rawichote Chalodhorn; David B. Grimes; Keith Grochow; Rajesh P. N. Rao (Adv. Robotics, 2010)

Entropy, the Indus Script, and Language: A Reply to R. Sproat. - Rajesh P. N. Rao; Nisha Yadav; Mayank N. Vahia; Hrishikesh Joglekar; Ronojoy Adhikari; Iravatham Mahadevan (Comput. Linguistics, 2010)

Probabilistic Analysis of an Ancient Undeciphered Script. - Rajesh P. N. Rao (Computer, 2010)

Large Margin Boltzmann Machines and Large Margin Sigmoid Belief Networks - Xu Miao; Rajesh P. N. Rao (CoRR, 2010)

Decision Making Under Uncertainty: A Neural Model Based on Partially Observable Markov Decision Processes. - Rajesh P. N. Rao (Frontiers Comput. Neurosci., 2010)

"Social" robots are psychological agents for infants: A test of gaze following. - Andrew N. Meltzoff; Rechele Brooks; Aaron P. Shon; Rajesh P. N. Rao (Neural Networks, 2010)

Brain-Computer Interfacing [In the Spotlight]. - Rajesh P. N. Rao; Reinhold Scherer (IEEE Signal Process. Mag., 2010)

Learning to Imitate Human Actions through Eigenposes. - Rawichote Chalodhorn; Rajesh P. N. Rao (From Motor Learning to Interaction Learning in Robots, 2010)

Gaze Following as Goal Inference: A Bayesian Model. - Abram L. Friesen; Rajesh P. N. Rao (CogSci, 2011)

An adaptive brain-computer interface for humanoid robot control. - Matthew J. Bryan; Joshua Green; Mike Chung 001; Lillian Y. Chang; Reinhold Scherer; Joshua R. Smith 001; Rajesh P. N. Rao (Humanoids, 2011)

A Hierarchical Architecture for Adaptive Brain-Computer Interfacing. - Mike Chung 001; Willy Cheung; Reinhold Scherer; Rajesh P. N. Rao (IJCAI, 2011)

Non-invasive Brain-Computer Interfaces: Enhanced Gaming and Robotic Control. - Reinhold Scherer; Elisabeth C. V. Friedrich; Brendan Z. Allison; Markus Pröll; Mike Chung 001; Willy Cheung; Rajesh P. N. Rao; Christa Neuper (IWANN (1), 2011)

Simultaneous brain-computer interfacing and motor control: Expanding the reach of non-invasive BCIs. - Willy Cheung; Devapratim Sarma; Reinhold Scherer; Rajesh P. N. Rao (EMBC, 2012)

Automatic extraction of command hierarchies for adaptive brain-robot interfacing. - Matthew J. Bryan; Griffin Nicoll; Vibinash Thomas; Mike Chung 001; Joshua R. Smith 001; Rajesh P. N. Rao (ICRA, 2012)

How Prior Probability Influences Decision Making: A Unifying Probabilistic Model. - Yanping Huang; Abram L. Friesen; Timothy D. Hanks; Michael N. Shadlen; Rajesh P. N. Rao (NIPS, 2012)

Fast Structured Prediction Using Large Margin Sigmoid Belief Networks. - Xu Miao; Rajesh P. N. Rao (Int. J. Comput. Vis., 2012)

Complementary Kernel Density Estimation. - Xu Miao; Ali Rahimi; Rajesh P. N. Rao (Pattern Recognit. Lett., 2012)

Non-intrusive tongue machine interface. - Qiao Zhang 001; Shyamnath Gollakota; Ben Taskar; Raj P. N. Rao (CHI, 2014)

Robot Programming by Demonstration with Crowdsourced Action Fixes. - Maxwell Forbes; Michael Jae-Yoon Chung; Maya Cakmak; Rajesh P. N. Rao (HCOMP, 2014)

Accelerating imitation learning through crowdsourcing. - Michael Jae-Yoon Chung; Maxwell Forbes; Maya Cakmak; Rajesh P. N. Rao (ICRA, 2014)

Neurons as Monte Carlo Samplers: Bayesian Inference and Learning in Spiking Networks. - Yanping Huang; Rajesh P. N. Rao (NIPS, 2014)

Broadband changes in the cortical surface potential track activation of functionally diverse neuronal populations. - Kai J. Miller; Christopher J. Honey; Dora Hermes; Rajesh P. N. Rao; Marcel den Nijs; Jeffrey G. Ojemann (NeuroImage, 2014)

Exploring the Potential of Information Gathering Robots. - Michael Jae-Yoon Chung; Andrzej Pronobis; Maya Cakmak; Dieter Fox; Rajesh P. N. Rao (HRI (Extended Abstracts), 2015)

Robot Programming by Demonstration with situated spatial language understanding. - Maxwell Forbes; Rajesh P. N. Rao; Luke Zettlemoyer; Maya Cakmak (ICRA, 2015)

Designing information gathering robots for human-populated environments. - Michael Jae-Yoon Chung; Andrzej Pronobis; Maya Cakmak; Dieter Fox; Rajesh P. N. Rao (IROS, 2015)

Near-Instantaneous Classification of Perceptual States from Cortical Surface Recordings. - Kai J. Miller; Gerwin Schalk; Dora Hermes; Jeffrey G. Ojemann; Rajesh P. N. Rao (Brain-Computer Interface Research (4), 2015)

Multistep model for predicting upper-limb 3D isometric force application from pre-movement electrocorticographic features. - Jing Wu 015; Benjamin R. Shuman; Bingni W. Brunton; Katherine M. Steele; Jared D. Olson; Rajesh P. N. Rao; Jeffrey G. Ojemann (EMBC, 2016)

Initiative in Robot Assistance during Collaborative Task Execution. - Jimmy Baraglia; Maya Cakmak; Yukie Nagai; Rajesh P. N. Rao; Minoru Asada (HRI, 2016)

Autonomous question answering with mobile robots in human-populated environments. - Michael Jae-Yoon Chung; Andrzej Pronobis; Maya Cakmak; Dieter Fox; Rajesh P. N. Rao (IROS, 2016)

Navigating a 2D Virtual World Using Direct Brain Stimulation. - Darby M. Losey; Andrea Stocco 002; Justin A. Abernethy; Rajesh P. N. Rao (Frontiers Robotics AI, 2016)

Bayesian Inference and Online Learning in Poisson Neuronal Networks. - Yanping Huang; Rajesh P. N. Rao (Neural Comput., 2016)

Spontaneous Decoding of the Timing and Content of Human Object Perception from Cortical Surface Recordings Reveals Complementary Information in the Event-Related Potential and Broadband Spectral Change. - Kai J. Miller; Gerwin Schalk; Dora Hermes; Jeffrey G. Ojemann; Rajesh P. N. Rao (PLoS Comput. Biol., 2016)

Cortico-Cortical Interactions during Acquisition and Use of a Neuroprosthetic Skill. - Jeremiah D. Wander; Devapratim Sarma; Lise A. Johnson; Eberhard E. Fetz; Rajesh P. N. Rao; Jeffrey G. Ojemann; Felix Darvas (PLoS Comput. Biol., 2016)

New Perspectives on Neuroengineering and Neurotechnologies: NSF-DFG Workshop Report. - Chet T. Moritz; Patrick Ruther; Sara Goering; Alfred Stett; Tonio Ball; Wolfram Burgard; Eric H. Chudler; Rajesh P. N. Rao (IEEE Trans. Biomed. Eng., 2016)

Task-Specific Somatosensory Feedback via Cortical Stimulation in Humans. - Jeneva A. Cronin; Jing Wu 015; Kelly L. Collins; Devapratim Sarma; Rajesh P. N. Rao; Jeffrey G. Ojemann; Jared D. Olson (IEEE Trans. Haptics, 2016)

Learning deep generative spatial models for mobile robots. - Andrzej Pronobis; Rajesh P. N. Rao (IROS, 2017)

Interactive web application for exploring matrices of neural connectivity. - David J. Caldwell; Jing Wu 015; Kaitlyn Casimo; Jeffrey G. Ojemann; Rajesh P. N. Rao (NER, 2017)

Electrocorticographic dynamics predict visually guided motor imagery of grasp shaping. - Jing Wu 015; Kaitlyn Casimo; David J. Caldwell; Rajesh P. N. Rao; Jeffrey G. Ojemann (NER, 2017)

Learning Semantic Maps with Topological Spatial Relations Using Graph-Structured Sum-Product Networks. - Kaiyu Zheng; Andrzej Pronobis; Rajesh P. N. Rao (CoRR, 2017)

Transformational Sparse Coding. - Dimitrios C. Gklezakos; Rajesh P. N. Rao (CoRR, 2017)

Efficient human-robot collaboration: When should a robot take initiative? - Jimmy Baraglia; Maya Cakmak; Yukie Nagai; Rajesh P. N. Rao; Minoru Asada (Int. J. Robotics Res., 2017)

AJILE Movement Prediction: Multimodal Deep Learning for Natural Human Neural Recordings and Video. - Nancy Xin Ru Wang; Ali Farhadi; Rajesh P. N. Rao; Bingni W. Brunton (AAAI, 2018)

Learning Graph-Structured Sum-Product Networks for Probabilistic Semantic Maps. - Kaiyu Zheng; Andrzej Pronobis; Rajesh P. N. Rao (AAAI, 2018)

Electrocorticographic Dynamics Predict Sustained Grasping and Upper-Limb Kinetic Output. - Katie Ly; Jing Wu 015; Lila Levinson; Benjamin R. Shuman; Katherine M. Steele; Jeffrey G. Ojemann; Rajesh P. N. Rao (SMC, 2018)

BrainNet: A Multi-Person Brain-to-Brain Interface for Direct Collaboration Between Brains. - Linxing Jiang; Andrea Stocco 002; Darby M. Losey; Justin A. Abernethy; Chantel S. Prat; Rajesh P. N. Rao (CoRR, 2018)

Towards Neural Co-Processors: Combining Neural Decoding and Encoding in Brain-Computer Interfaces. - Rajesh P. N. Rao (CoRR, 2018)

The Indus Script and Economics. A Role for Indus Seals and Tablets in Rationing and Administration of Labor. - Rajesh P. N. Rao (CoRR, 2018)

Estimation of Vector Autoregressive Parameters and Granger Causality From Noisy Multichannel Data. - Prashant Rangarajan; Rajesh P. N. Rao (IEEE Trans. Biomed. Eng., 2019)

Unsupervised Sleep and Wake State Identification in Long-Term Electrocorticography Recordings. - Samantha Sun; Linxing Preston Jiang; Steven M. Peterson; Jeffrey Herron; Kurt E. Weaver; Andrew L. Ko; Jeffrey G. Ojemann; Rajesh P. N. Rao (EMBC, 2020)

Understanding biological plume tracking behavior using deep reinforcement-learning. - Satpreet H. Singh; Floris van Breugel; Rajesh P. N. Rao; Bingni W. Brunton (ALIFE, 2020)

Towards naturalistic human neuroscience and neuroengineering: behavior mining in long-term video and neural recordings. - Satpreet H. Singh; Steven M. Peterson; Rajesh P. N. Rao; Bingni W. Brunton (CoRR, 2020)

Brain Co-Processors: Using AI to Restore and Augment Brain Function. - Rajesh P. N. Rao (CoRR, 2020)

A Platform for Virtual Reality Task Design with Intracranial Electrodes. - Maurice Montag; Courtnie Paschall; Jeffrey G. Ojemann; Rajesh P. N. Rao; Jeffrey Herron (EMBC, 2021)

Emergent behavior and neural dynamics in artificial agents tracking turbulent plumes. - Satpreet Harcharan Singh; Floris van Breugel; Rajesh P. N. Rao; Bingni Wen Brunton (CoRR, 2021)

An Immersive Virtual Reality Platform Integrating Human ECOG & sEEG: Implementation & Noise Analysis. - Courtnie Paschall; Rajesh P. N. Rao; Jason S. Hauptman; Jeffrey G. Ojemann; Jeffrey Herron (EMBC, 2022)

Repairing Brain-Computer Interfaces with Fault-Based Data Acquisition. - Cailin Winston; Caleb Winston; Chloe N. Winston; Claris Winston; Cleah Winston; Rajesh P. N. Rao; René Just (ICSE, 2022)

Touching the Void: Intracranial Stimulation for NeuroHaptic Feedback in Virtual Reality. - Courtnie Jean Paschall; Jason S. Hauptman; Rajesh P. N. Rao; Jeffrey G. Ojemann; Jeffrey Herron (SMC, 2022)

Human intracortical responses to varying electrical stimulation conditions are separable in low-dimensional subspaces. - Samantha Sun; Lila H. Levinson; Courtnie Jean Paschall; Jeffrey Herron; Kurt E. Weaver; Jason S. Hauptman; Andrew Ko; Jeffrey G. Ojemann; Rajesh P. N. Rao (SMC, 2022)

Active Predictive Coding Networks: A Neural Solution to the Problem of Learning Reference Frames and Part-Whole Hierarchies. - Dimitrios C. Gklezakos; Rajesh P. N. Rao (CoRR, 2022)

Recursive Neural Programs: Variational Learning of Image Grammars and Part-Whole Hierarchies. - Ares Fisher; Rajesh P. N. Rao (CoRR, 2022)

Hyper-Universal Policy Approximation: Learning to Generate Actions from a Single Image using Hypernets. - Dimitrios C. Gklezakos; Rishi Jha; Rajesh P. N. Rao (CoRR, 2022)

Neural Co-Processors for Restoring Brain Function: Results from a Cortical Model of Grasping. - Matthew J. Bryan; Linxing Preston Jiang; Rajesh P. N. Rao (CoRR, 2022)

Dynamic Predictive Coding Explains Both Prediction and Postdiction in Visual Motion Perception. - Linxing Preston Jiang; Rajesh P. N. Rao (CogSci, 2023)

Active Predictive Coding: A Unified Neural Framework for Learning Hierarchical World Models for Perception and Planning. - Rajesh P. N. Rao; Dimitrios C. Gklezakos; Vishwas Sathish (CogSci, 2023)

Expressive probabilistic sampling in recurrent neural networks. - Shirui Chen; Linxing Jiang; Rajesh P. N. Rao; Eric Shea-Brown (NeurIPS, 2023)

Brain-Inspired Computational Intelligence via Predictive Coding. - Tommaso Salvatori; Ankur Arjun Mali; Christopher L. Buckley; Thomas Lukasiewicz; Rajesh P. N. Rao; Karl J. Friston; Alexander Ororbia (CoRR, 2023)

Expressive probabilistic sampling in recurrent neural networks. - Shirui Chen; Linxing Preston Jiang; Rajesh P. N. Rao; Eric Shea-Brown (CoRR, 2023)

Culturally-Attuned Moral Machines: Implicit Learning of Human Value Systems by AI through Inverse Reinforcement Learning. - Nigini Oliveira; Jasmine Li; Koosha Khalvati; Rodolfo Cortes Barragan; Katharina Reinecke; Andrew N. Meltzoff; Rajesh P. N. Rao (CoRR, 2023)

Emergent behaviour and neural dynamics in artificial agents tracking odour plumes. - Satpreet H. Singh; Floris van Breugel; Rajesh P. N. Rao; Bingni W. Brunton (Nat. Mac. Intell., 2023)

Active Predictive Coding: A Unifying Neural Model for Active Perception, Compositional Learning, and Hierarchical Planning. - Rajesh P. N. Rao; Dimitrios C. Gklezakos; Vishwas Sathish (Neural Comput., 2024)

Dynamic predictive coding: A model of hierarchical sequence learning and prediction in the neocortex. - Linxing Preston Jiang; Rajesh P. N. Rao (PLoS Comput. Biol., 2024)

Meta-Representational Predictive Coding: Biomimetic Self-Supervised Learning. - Alexander Ororbia; Karl J. Friston; Rajesh P. N. Rao (CoRR, 2025)

Temporal Basis Function Models for Closed-Loop Neural Stimulation. - Matthew J. Bryan; Felix Schwock; Azadeh Yazdan-Shahmorad; Rajesh P. N. Rao (CoRR, 2025)